Predictive modeling of bankruptcy with an emphasis on modern measurement methods

Document Type : Original Article

Authors
Mohammadreza Nosratnezami 1
Fazel Mohammadi Nodeh 2
sina kherdyar 3
1 PhD candidate in Financial Engineering, Financial Engineering Department, Rasht branch, Islamic Azad University, Rasht, Iran.
2 Assistant Professor, Department of Management, lahijan Branch, Islamic Azad University, Lahijan, Iran
3 Associate professor, Department of Accounting, Rasht branch, Islamic Azad University, Rasht, Iran.
10.30495/jik.2025.23649
Abstract
The purpose of this research is to use a combination of a systematic review and the Fuzzy Delphi approach to Abstract:
The purpose of this research is to use a combination of a systematic review and the Fuzzy Delphi approach to identify the effective factors and models in the bankruptcy of listed companies on the Tehran Stock Exchange. Literature of the bankruptcy prediction has extensively examined for public joint-stock companies, but no systematic study or any other form of literature review has been conducted on manufacturing companies in economies undergoing dissolution. This research contributes new knowledge by predicting bankruptcy for manufacturing companies in developing economies. The MAX QDA software was used to analyze the qualitative data obtained from research interviews. The results of coding from the research interviews were identified, and nearly 30 codes were extracted in this regard. In the axial coding, discrete concepts are arranged next to each other in a meaningful framework, which identifies the relationships among them, especially relation of axial concept with other concepts. Results from this research suggest that using the new structures such as combined intelligent systems based on the datamining models has high ability in identifying bankruptcy of companies nationwide. This research utilizes modern measurement methods such as Artificial Neural Network algorithms and Support Vector Machines and applied data are generalized to two industries namely food and textile and this research data are not limited to the companies listed on Tehran Stock Exchange.
Keywords
" Bankruptcy"
"New methods of measurement"
" Artificial Neural Network"
"Support Vector Machine"
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